Knowledge Representation for Agents and Multi-Agent Systems
Knowledge Representation for Agents and Multi-Agent Systems

Author: John-Jules Meyer

Publisher: Springer

Published: 2009-10-13

Total Pages: 168

ISBN-13: 3642053017

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This book constitutes the thoroughly refereed post-workshop proceedings of the First International Workshop on Knowledge Representation for Agents and Multi-Agent Systems, KRAMAS 2008, held in Sydney, Australia, in September 2008 as a satellite event of KR 2008, the 11th International Conference on Principles of Knowledge Representation and Reasoning. The 10 revised full papers presented were carefully reviewed and selected from 14 submissions. The papers foster the cross-fertilization between the KR (knowledge representation and reasoning) and agent communities, by discussing knowledge representation theories and techniques for agent-based systems.

Adaptive Agents and Multi-Agent Systems
Adaptive Agents and Multi-Agent Systems

Author: Eduardo Alonso

Publisher: Springer Science & Business Media

Published: 2003-04-23

Total Pages: 335

ISBN-13: 3540400680

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Adaptive Agents and Multi-Agent Systems is an emerging and exciting interdisciplinary area of research and development involving artificial intelligence, computer science, software engineering, and developmental biology, as well as cognitive and social science. This book surveys the state of the art in this emerging field by drawing together thoroughly selected reviewed papers from two related workshops; as well as papers by leading researchers specifically solicited for this book. The articles are organized into topical sections on - learning, cooperation, and communication - emergence and evolution in multi-agent systems - theoretical foundations of adaptive agents

Engineering Multi-Agent Systems
Engineering Multi-Agent Systems

Author: Matteo Baldoni

Publisher: Springer

Published: 2016-12-15

Total Pages: 239

ISBN-13: 3319509837

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This book constitutes revised, selected, and invited papers from the 4th International Workshop on Engineering Multi-Agent Systems, EMAS 2016, held in Singapore, in May 2016, in conjunction with AAMAS. The 10 full papers presented in this volume were carefully reviewed and selected from 14 submissions. The book also contains 2 invited papers; extended versions of AAMAS 2016 demonstration abstracts. EMAS deals with MAS software engineering processes, methodologies and techniques; Programming languages for MAS; Formal methods and declarative technologies for the specification, validation and verification of MAS; and development tools.

Multiagent Systems
Multiagent Systems

Author: Gerhard Weiss

Publisher: MIT Press

Published: 2013-03-08

Total Pages: 917

ISBN-13: 0262018896

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This is the first comprehensive introduction to multiagent systems and contemporary distributed artificial intelligence that is suitable as a textbook.

Knowledge Representation for Agents and Multi-agent Systems
Knowledge Representation for Agents and Multi-agent Systems

Author:

Publisher:

Published: 2009

Total Pages: 0

ISBN-13: 9788364205309

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This book constitutes the thoroughly refereed post-workshop proceedings of the First International Workshop on Knowledge Representation for Agents and Multi-Agent Systems, KRAMAS 2008, held in Sydney, Australia, in September 2008 as a satellite event of KR 2008, the 11th International Conference on Principles of Knowledge Representation and Reasoning. The 10 revised full papers presented were carefully reviewed and selected from 14 submissions. The papers foster the cross-fertilization between the KR (knowledge representation and reasoning) and agent communities, by discussing knowledge representation theories and techniques for agent-based systems.

Autonomous Agents and Multi-agent Systems
Autonomous Agents and Multi-agent Systems

Author: Jiming Liu

Publisher: World Scientific

Published: 2001

Total Pages: 302

ISBN-13: 9810242824

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An autonomous agent is a computational system that acquires sensory data from its environment and decides by itself how to relate the external stimulus to its behaviors in order to attain certain goals. Responding to different stimuli received from its task environment, the agent may select and exhibit different behavioral patterns. The behavioral patterns may be carefully predefined or dynamically acquired by the agent based on some learning and adaptation mechanism(s). In order to achieve structural flexibility, reliability through redundancy, adaptability, and reconfigurability in real-world tasks, some researchers have started to address the issue of multiagent cooperation. Broadly speaking, the power of autonomous agents lies in their ability to deal with unpredictable, dynamically changing environments. Agent-based systems are becoming one of the most important computer technologies, holding out many promises for solving real-world problems. The aims of this book are to provide a guided tour to the pioneering work and the major technical issues in agent research, and to give an in-depth discussion on the computational mechanisms for behavioral engineering in autonomous agents. Through a systematic examination, the book attempts to provide the general design principles for building autonomous agents and the analytical tools for modeling the emerged behavioral properties of a multiagent system.

A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence
A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence

Author: Nikos Kolobov

Publisher: Springer Nature

Published: 2022-06-01

Total Pages: 71

ISBN-13: 3031015436

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Multiagent systems is an expanding field that blends classical fields like game theory and decentralized control with modern fields like computer science and machine learning. This monograph provides a concise introduction to the subject, covering the theoretical foundations as well as more recent developments in a coherent and readable manner. The text is centered on the concept of an agent as decision maker. Chapter 1 is a short introduction to the field of multiagent systems. Chapter 2 covers the basic theory of singleagent decision making under uncertainty. Chapter 3 is a brief introduction to game theory, explaining classical concepts like Nash equilibrium. Chapter 4 deals with the fundamental problem of coordinating a team of collaborative agents. Chapter 5 studies the problem of multiagent reasoning and decision making under partial observability. Chapter 6 focuses on the design of protocols that are stable against manipulations by self-interested agents. Chapter 7 provides a short introduction to the rapidly expanding field of multiagent reinforcement learning. The material can be used for teaching a half-semester course on multiagent systems covering, roughly, one chapter per lecture.

Handbook of Knowledge Representation
Handbook of Knowledge Representation

Author: Frank van Harmelen

Publisher: Elsevier

Published: 2008-01-08

Total Pages: 1035

ISBN-13: 0080557023

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Handbook of Knowledge Representation describes the essential foundations of Knowledge Representation, which lies at the core of Artificial Intelligence (AI). The book provides an up-to-date review of twenty-five key topics in knowledge representation, written by the leaders of each field. It includes a tutorial background and cutting-edge developments, as well as applications of Knowledge Representation in a variety of AI systems. This handbook is organized into three parts. Part I deals with general methods in Knowledge Representation and reasoning and covers such topics as classical logic in Knowledge Representation; satisfiability solvers; description logics; constraint programming; conceptual graphs; nonmonotonic reasoning; model-based problem solving; and Bayesian networks. Part II focuses on classes of knowledge and specialized representations, with chapters on temporal representation and reasoning; spatial and physical reasoning; reasoning about knowledge and belief; temporal action logics; and nonmonotonic causal logic. Part III discusses Knowledge Representation in applications such as question answering; the semantic web; automated planning; cognitive robotics; multi-agent systems; and knowledge engineering. This book is an essential resource for graduate students, researchers, and practitioners in knowledge representation and AI. * Make your computer smarter* Handle qualitative and uncertain information* Improve computational tractability to solve your problems easily

Knowledge Representation, Reasoning, and the Design of Intelligent Agents
Knowledge Representation, Reasoning, and the Design of Intelligent Agents

Author: Michael Gelfond

Publisher: Cambridge University Press

Published: 2014-03-10

Total Pages: 363

ISBN-13: 1107782872

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Knowledge representation and reasoning is the foundation of artificial intelligence, declarative programming, and the design of knowledge-intensive software systems capable of performing intelligent tasks. Using logical and probabilistic formalisms based on answer set programming (ASP) and action languages, this book shows how knowledge-intensive systems can be given knowledge about the world and how it can be used to solve non-trivial computational problems. The authors maintain a balance between mathematical analysis and practical design of intelligent agents. All the concepts, such as answering queries, planning, diagnostics, and probabilistic reasoning, are illustrated by programs of ASP. The text can be used for AI-related undergraduate and graduate classes and by researchers who would like to learn more about ASP and knowledge representation.

Readings in Agents
Readings in Agents

Author: Michael N. Huhns

Publisher: Morgan Kaufmann

Published: 1998

Total Pages: 552

ISBN-13: 9781558604957

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This book collects the most significant literature on agents in an attempt top forge a broad foundation for the field. Includes papers from the perspectives of AI, databases, distributed computing, and programming languages. The book will be of interest to programmers and developers, especially in Internet areas.